Triple
T14071107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paul Prenter |
E338608
|
entity |
| Predicate | allegedlySoldStoriesTo |
P105243
|
FINISHED |
| Object | British tabloids |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: British tabloids | Statement: [Paul Prenter, allegedlySoldStoriesTo, British tabloids]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: allegedlySoldStoriesTo Context triple: [Paul Prenter, allegedlySoldStoriesTo, British tabloids]
-
A.
someAssetsSoldTo
Indicates that a subset of an entity’s assets has been transferred in ownership to another party through a sale.
-
B.
soldWorkTo
chosen
Indicates that one entity transferred ownership of a work (such as a product, artwork, or creation) to another entity in exchange for payment.
-
C.
soldWellIn
Indicates that something achieved strong sales performance within a particular market, region, or time period.
-
D.
soldTechnologyTo
Indicates that one entity transferred ownership or rights to a technology to another entity in exchange for compensation.
-
E.
hasInfluentialStory
Indicates that one entity possesses or is associated with a story that significantly shapes, impacts, or guides the beliefs, actions, or development of another entity.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d81c67ba6c819091935650dfb3b895 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5c5aa828819098ef55a70a0decbc |
completed | April 14, 2026, 3:25 p.m. |
| PD | Predicate disambiguation | batch_69de05adef888190b023ab42ef5076b6 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:21 p.m.